{"id":"W4303613618","doi":"10.3390/buildings12101608","title":"Improvisation in Construction Planning: An Agent-Based Simulation Approach","year":2022,"lang":"en","type":"article","venue":"Buildings","topic":"Construction Project Management and Performance","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; American University of Beirut","keywords":"Improvisation; Process (computing); Computer science; Planner; Process management; Management science; Perspective (graphical); Engineering; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006045976,0.00061457,0.0006824463,0.0005815075,0.0006909377,0.001542666,0.001406836,0.001421603,0.002522745],"category_scores_gemma":[0.002090568,0.0004700567,0.0007102381,0.0005568306,0.0008693148,0.000981806,0.001083866,0.001037592,0.0001916247],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001597135,"about_ca_system_score_gemma":0.001912278,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02084006,"about_ca_topic_score_gemma":0.0161125,"domain_scores_codex":[0.9995826,0.0002560147,0.00001544961,0.00004626743,0.00005802909,0.00004162463],"domain_scores_gemma":[0.9987574,0.0009396814,0.00009933598,0.00004615232,0.00009061876,0.0000668599],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002298266,0.00003301644,0.0004302652,0.00001588061,0.00001495793,0.00002447537,0.00007194986,0.9938036,0.0001959502,0.003918956,0.00005692192,0.001410997],"study_design_scores_gemma":[0.000008921807,0.00001610975,0.0000619214,0.000004426511,0.000004924402,0.000003283799,0.00002410788,0.998248,0.00006873077,0.001264277,0.0002909571,0.000004366867],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3037173,0.000493456,0.6616942,0.001029064,0.00008429429,0.0004095421,0.0002974213,0.0004395275,0.03183514],"genre_scores_gemma":[0.9219075,0.0003774806,0.07348394,0.0000589907,0.00001713422,0.0003995218,0.0001379976,0.00002854694,0.003588744],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02084006,"threshold_uncertainty_score":0.04143751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1377573300002012,"score_gpt":0.3906547384589313,"score_spread":0.25289740845873,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}